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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Provably-Stable Overload Ride-Through Control for Grid-Forming Inverters Using System-Wide Lyapunov Function Analysis

A key challenge associated with a grid-forming (GFM) inverter based resource (IBR) is its behavior during severe grid disturbances: since a GFM inverter regulates voltage in the fast timescale instead of current or power, it may experience a transient overload of current, power and/or energy during a severe grid disturbance. While many promising control strategies for overload ride-through have been proposed over the past two decades, transient stability of the system during and after the transition to an overload ride-through control mode remains difficult to guarantee. In this work, a novel overload ride-through control strategy is proposed for a system of grid-forming inverters that takes both self-protection and system-wide transient stability into account. A proposed system-level supervisory control uses slow communication to pre-emptively assign a set of local ride through control parameters to individual GFM IBR, including a current-limiting virtual reactance, that guarantees that synchronism is still preserved for any set of anticipated grid disturbances. At the core of the supervisory control lies a Lyapunov-function-based routine capable of establishing a strong, albeit conservative, transient stability guarantee for the system. Here, the proposed overload ride-through control strategy is validated via numerical integration of a reduced-order model, as well as through detailed electromagnetic transient (EMT) simulation.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models

Visualization and analysis of multivariate data and their uncertainty are top research challenges in data visualization. Constructing fiber surfaces is a popular technique for multivariate data visualization that generalizes the idea of level-set visualization for univariate data to multivariate data. Here, in this paper, we present a statistical framework to quantify positional probabilities of fibers extracted from uncertain bivariate fields. Specifically, we extend the state-of-the-art Gaussian models of uncertainty for bivariate data to other parametric distributions (e.g., uniform and Epanechnikov) and more general nonparametric probability distributions (e.g., histograms and kernel density estimation) and derive corresponding spatial probabilities of fibers. In our proposed framework, we leverage Green's theorem for closed-form computation of fiber probabilities when bivariate data are assumed to have independent parametric and nonparametric noise. Additionally, we present a nonparametric approach combined with numerical integration to study the positional probability of fibers when bivariate data are assumed to have correlated noise. For uncertainty analysis, we visualize the derived probability volumes for fibers via volume rendering and extracting level sets based on probability thresholds. We present the utility of our proposed techniques via experiments on synthetic and simulation datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Development and Validation of Passive Yaw in the Open-Source WEC-Sim Code

A passive yaw implementation is developed, validated, and explored for the WEC-Sim, an open-source wave energy converter modeling tool that works within MATLAB/Simulink. The Reference Model 5 (RM5) is selected for this investigation, and a WEC-Sim model of the device is modified to allow yaw motion. A boundary element method (BEM) code was used to calculate the excitation force coefficients for a range of wave headings. An algorithm was implemented in WEC-Sim to determine the equivalent wave heading from a body’s instantaneous yaw angle and interpolate the appropriate excitation coefficients to ensure the correct time-domain excitation force. This approach is able to determine excitation force for a body undergoing large yaw displacement. For the mathematically simple case of regular wave excitation, the dynamic equation was integrated numerically and found to closely approximate the results from this implementation in WEC-Sim. A case study is presented for the same device in irregular waves. In this case, computation time is increased by 32x when this interpolation is performed at every time step. To reduce this expense, a threshold yaw displacement can be set to reduce the number of interpolations performed. A threshold of 0.01° was found to increase computation time by only 22x without significantly affecting time domain results. Similar amplitude spectra for yaw force and displacements are observed for all threshold values less than 1°, for which computation time is only increased by 2.2x.

50 EE - Wind and Water Power Program - Water (EE-4↗
DOE OSTI2020

Analytic stability boundaries for compressional and global Alfven eigenmodes driven by fast ions. II. Interaction via Landau resonance.

Conditions for net fast ion drive are derived for beam-driven, co-propagating, sub-cyclotron compressional (CAE) and global (GAE) Alfven eigenmodes driven by the Landau resonance with super-Alfvenic fast ions. Approximations applicable to realistic neutral beam distributions and mode characteristics observed in spherical tokamaks enable the derivation of marginal stability conditions for these modes. Such conditions successfully reproduce the stability boundaries found from numerical integration of the exact expression for local fast ion drive/damping. Coupling between the CAE and GAE branches of the dispersion due to finite \omega/\omega_{ci} and k_\parallel/k_\perp is retained and found to be responsible for the existence of the GAE instability via this resonance. Encouraging agreement is demonstrated between the approximate stability criterion, simulation results, and a database of NSTX observations of co-CAEs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Bug fixes / enhancements to Parallel tempering Markov chain Monte Carlo sampler (PTMCMCSampler) v3

Markov chain Monte Carlo sampler useful for a variety of problems for optimization, numerical integration, and generating draws from a probability distribution. They are often used in physical and mathematical problems, especially when it is difficult or impossible to use other approaches. This disclosure is for new bug fixes and enhancements to an existing open source library that is already in the public domain under the MIT license. https://github.com/jellis18/PTMCMCSampler

Forrer, Mark↗
DOE OSTI2026

Kinetic Model of HoxEFU reduction by NADH [SWR-26-087]

This repository is used to release code generated for manuscripts on the Photosynthetic Energy Transduction core program. This code simulates the reduction of HoxEFU by NADH. The electro transfer rate constants for the simulation are specified in the .csv files. The two .csv files correspond tot he two models described in Dawson et al. Cell. Rep. Phys. Sci. 2026. The code utilizes a chemical master equation, a set of differential equations, defining the time evolution of the oxidation and reduction kinetics of NAD+, NADH, a FMN flavin, and a set of iron sulfur clusters. The kinetics of HoxEFU reduction by NADH are evaluated by numerical integration of the chemical master equation using a variable-time-step Runge-Kutta algorithm.

Dahl, Peter [National Laboratory of the Rockies (N↗
DOE OSTI2022

Theory of In-Cloud Activation of Aerosols and Microphysical Quasi-Equilibrium in a Deep Updraft

The microphysical quasi-equilibrium in an ascending adiabatic parcel is elucidated by an analytical theory in 0D with drastic simplifications. The theory predicts how in-cloud activation is most likely to be triggered by the onset of precipitation during sufficient ascent, with the ascent only needing to approach almost twice the cloud-base updraft speed aloft. The precipitation and cloud condensate mass fields are coupled in a closed system in a simplified version of the model. The initial state of no precipitation is unstable with respect to a perturbation. In the 2D phase space of both mass fields, there is a neutral line. Unstable growth of precipitation mass drives the system to cross the line into a regime of stability. An attractor is then approached consisting of precipitation mass balanced by accretion of cloud mass and fallout. The cloud-particle number concentration also approaches a stable equilibrium governed by the balance between in-cloud activation aloft from the inexorably increasing supersaturation during vertical acceleration and accretion of cloud droplets by precipitation. Dimensionless numbers characterizing the microphysical equilibria and their stability are derived mathematically, including a condensation–precipitation efficiency and an in-cloud activation efficiency. The theory explains common observations of the orders of magnitude of liquid water content in convective and stratiform clouds. Finally, sensitivity tests of the numerically integrated theoretical equations are documented with respect to variations in cloud condensation nucleus (CCN) aerosols and updraft speed. In conclusion, it is shown that this theory of in-cloud activation, with an increasing supersaturation during ascent, applies to both ice-only and liquid-only cloud.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Analytic phase solutions of three-wave interactions

Closed-form analytic phase solutions of three-wave interactions are presented for the first time. The cases from simple second harmonic generation to most general three wave interactions without any constraints are considered. The phase amplification or deamplification behavior in the phase-sensitive parametric process is illustrated using the results obtained here. The analytic solutions agree with the results from direct numerical integration. The validity range of an approximate phase solution is discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Utah FORGE: Optimization of a Plug-and-Perf Stimulation (Fervo Energy)

Information around the plug-and-perf treatment design at Utah FORGE by Fervo Energy. Objective and Purpose: - Develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS system: i) Achieving sufficient injectivity to support high cross-well flow rates ii) Distributing flow evenly across the wellbore and reservoir to maximize heat mining efficiency, ensure sustained heat transfer, and mitigate thermal breakthrough iii) Overcoming the effects of stress heterogeneity, stress shadowing, and variations in natural fracture properties during the stimulation treatment, leading to a more predictable stimulated reservoir volume and offset well placement - The following activities will be performed: i) Design, plan, and execute a multistage plug-and-perf stimulation treatment at a Fervo site with data acquisition and well testing activities aimed at addressing key technical aspects of the issues above ii) Perform data processing and interpretation of field results to translate the results form the Fervo site to a site-specific design at the Utah FORGE site iii) Design, plan, and execute a multistage plug-and-perf stimulation treatment design at the Utah FORGE site Methods and Approach: - Design a detailed data acquisition plan to maximize learning around: i) DFIT testing ii) Petrophysical logging, image logging iii) Permanent DAS/DTS fiber optic monitoring iv) Deep borehole microseismic monitoring v) Shallow borehole induced seismicity monitoring vi) Injection/production testing (RTA analysis, tracer testing) vii) Integrated numerical modeling and production forecasting

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Machine learning for postprocessing ensemble streamflow forecasts

Skillful streamflow forecasts can inform decisions in various areas of water policy and management. We integrate numerical weather prediction ensembles, distributed hydrological model, and machine learning to generate ensemble streamflow forecasts at medium-range lead times (1–7 days). We demonstrate the application of machine learning as postprocessor for improving the quality of ensemble streamflow forecasts. Our results show that the machine learning postprocessor can improve streamflow forecasts relative to low-complexity forecasts (e.g., climatological and temporal persistence) as well as standalone hydrometeorological modeling and neural network. The relative gain in forecast skill from postprocessor is generally higher at medium-range timescales compared to shorter lead times; high flows compared to low–moderate flows, and the warm season compared to the cool ones. Overall, our results highlight the benefits of machine learning in many aspects for improving both the skill and reliability of streamflow forecasts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

SCEPTRE 2.2 Angular Quadrature Sets

This document includes details of the angular quadrature sets available in SCEPTRE for performing numerical integrations in the angular phase space. The angular dependence of the boundary and fixed-source terms an d initial angular flux are specified by angular index rather than by direction. It is, therefore, necessary to know the mapping from a specific direction to a direction index. This document includes angular quadrature weights and direction cosines for most of the quadrature sets available in SCEPTRE.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Vibration-Based Sensor Design: A Grey-Box Approach

Knowledge of the internal structure of an object or device under investigation proceeds from the basic idea of constructing its dynamic behavioral relations governed by a set of differential/algebraic equations that characterize its response. These equations can be partial differential equations leading to finite element or finite difference relations requiring a complex numerical solution on a super computer or ordinary differential equations requiring sophisticated numerical integration techniques to obtain the desired solution. Discrete dynamic systems evolving from digitized data acquisition are typically captured by sampled-data (continuous-to-discrete) representations characterized by a set of difference equations specifying the underlying system dynamics. In any case, with a mathematical description in hand, Grey-Box modeling techniques have evolved, concerned with the estimation of model parameters embedded in a prescribed set of equations (the system) governing its behavior, while capturing the underlying physical phenomenology of the problem at hand.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The woman behind the curious invention of modern software: Klára Dán von Neumann’s handwritten letters confirm her legacy

The year 1945 marked not only the birth of the atomic age, but also the birth of modern computer programming. The first fully electronic computing machine, the ENIAC (Electronic Numerical Integrator And Computer), came online in December 1945. But programming the ENIAC was an excruciatingly difficult task. Klára Dán von Neumann, who joined the Laboratory at Los Alamos after WWII, helped to revolutionize the process, creating the very first modern computer programs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Spark Channel Dynamics of Electrostatic Discharges

When two differently-charged objects are brought in close proximity to each other, the resulting high electric fields can cause electron avalanche breakdown of the air gap separating the objects, a process known as electrostatic discharge (ESD). If enough initial charge is stored on the objects, the electrical breakdown can proceed to ionize the air to such a degree that a highly conductive filament of plasma forms in the gap, known as a spark channel. The spark electrically bridges the air gap, resulting in a rapid pulse of current that neutralizes the charge difference. The current pulse produces significant heating of the gas in the spark, resulting in dissociation, ionization, thermal radiation, and hydrodynamic expansion. ESD presents a hazard to electrically-sensitive devices, with consequences such as economic losses (e.g. damaged electronics) or unsafe response (e.g. unintended ignition of flammable gas mixtures, initiation of detonators, etc.). For this thesis, the ESD spark is taken to occur between two conducting electrodes, with the spark channel being axisymmetric in a cylindrical coordinate system centered on the channel. An RLC-type circuit is used for the discharge model of the ESD event. The spark is treated as a time-dependent resistance that is in series with a capacitance, an inductance, and (optionally) a load resistance representing a “victim” component under threat from the ESD event. The primary motivation of this work is to use a numerical hydrodynamic model to understand the energy dissipation and transport processes in the spark. The model consists of the compressible Euler equations of mass, momentum, and energy conservation together with an Eddington/P1 approximation for thermal radiation transport. To close the hydrodynamic system, an equation of state (EOS) was fitted from tabular data for air that accounts for the dissociation and ionization of air species. The hydrodynamic equations are solved using a conservative Lagrangian finite volume method. These partial differential equations are coupled to the circuit equations by calculation of the spark resistance via numerical integration of the electrical conductivity of the channel. Computational results are compared against experimental measurements of discharge current and radial density of the spark channel.

42 ENGINEERING↗
DOE OSTI2023

Simulations Supporting the Development of Northstar's Indirect Beam Parameters Monitoring System

NorthStar Medical Radioisotopes, LLC is planning to produce the important medical radioisotope molybdenum-99 (Mo-99), the parent of technetium-99m (Tc-99m), through photonuclear reactions in molybdenum-100 (Mo-100). In this approach, a target comprising multiple thin disks of enriched molybdenum metal is bombarded with a 40-MeV electron beam. Electrons impinged on the molybdenum target produce bremsstrahlung X-rays that cause the nuclear reaction. Because enriched Mo-100 is expensive, there is a desire to utilize as much beam power as possible to achieve maximum production yield and minimize the size of the target. This requirement leads to very high beam power density (and heat deposition in the target), which creates challenging requirements for the cooling of the target. The critical part of the target is the target window. It separates the high-pressure helium cooled target from the vacuum beamline and the subject of structural and thermal stress. The temperature of the target window is proportional to the energy density deposited by the beam, so it is critical to maintain the desired beam profile on the target window. The feasibility of indirectly monitoring the maximum energy density of the beam on the beam window through beam losses at the main collimator (Collimator) before the production target was verified. A model of the NorthStar beam transport line was constructed for this purpose using MAD-X and Tao/Bmad codes. Beam optics were computed for the standard operational scenario, followed by an investigation involving approximately 400 cases with parameter variations in the last tuning quadrupoles. This was done to assess the correlation between losses in the collimator and the peak energy density on the target. We developed a model to explore the potential application of Optical transition radiation (OTR) for controlling beam parameters in the NorthStar beam delivery system. This model was based on a generic formula derived from the fundamental solution of the inhomogeneous wave equation of the vector potential, and allowed us to consider various surfaces, even those with irregular or random features, using numerical integration. We applied the model to OTR generated by relativistic electrons impacting an Inconel® 718 beam window. We examined cases with different levels of the window’s surface roughness, ranging from 0.5 to 3.0 microns of root square mean (RMS) deviation. The results of the OTR simulations provided distributions of OTR photons that can be used to study the limitations of optical systems for controlling beam parameters.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Expanding the representation of aerosol, cloud, and precipitation processes with graph network-based simulators

We explored a novel framework for simulating the small-scale processes that drive the evolution of aerosol, cloud, and precipitation particles, which are a critical gap in the predictive understanding of weather and climate. Particle-based methods have emerged as an effective tool for modeling aerosol-cloud-precipitation interactions, but existing particle-based models are computationally too expensive to simulate the large domains relevant for the atmosphere or to represent the full suite of relevant processes. The lack of a comprehensive and efficient reference model is a critical bottleneck in our understanding of cloud and precipitation processes and our ability to parameterize these processes for regional- and global-scale simulations. To address this need, we explored an approach to accelerate and expand particle-based models using a new machine learning approach, graph network-based simulators (GNS). Rather than modeling the evolution of the system by numerically integrating continuity equations, the GNS represents dynamics through learned message passing. Our aim was to develop fast and accurate surrogate models for particle-based simulations. We explored applying GNS to simulate cloud droplet transport, growth, and evaporation under turbulent conditions, but we found the GNS over-smoothed the simulations. We then applied the GNS to simulate aerosol dynamics through gas condensation and found the GNS was able to reproduce the benchmark, physics-based simulation with high accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Novel 'Smart Microchip Proppants' Technology for Precision Diagnostics of Hydraulic Fracture Networks (Edited Final Report)

This project introduces innovative technology to improve subsurface characterization, visualization, and diagnostics of unconventional reservoirs (fossil resources). Through a collaborative effort involving the University of Kansas, UCLA, MicroSilicon Inc., and EOG Resources, the project aims to deliver precision diagnostics for hydraulic fractures using novel high-resolution imaging technology based on smart microchip proppants. Additionally, it seeks to enhance the accuracy and predictability of integrated numerical, and machine-learning modeling techniques for hydraulic fracture characterization and simulation. This groundbreaking technology addresses significant gaps in understanding unconventional and tight reservoir behavior and optimizing well-completion strategies, enabling more cost-efficient recovery of unconventional resources.

02 PETROLEUM↗
DOE OSTI2025

Exact Timestep for a Pairwise Coulomb Collision

Standard numerical integrators work well for many-body Coulomb repulsion problems when the timestep is much shorter than the timescale of relative position changes. However, for ‘hard’ collisions in which two particles have a near miss and exchange a lot of momentum within one timestep, they understandably struggle. This note proposes using the exact solution of Keplerian two-body orbits (usually hyperbolic) to calculate the momentum exchange with other particles: either a selection of the ‘closest’ ones or all of them.

43 PARTICLE ACCELERATORS↗